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| Certification Vendor: | Databricks |
|---|---|
| Exam Name: | Databricks Certified Data Engineer Associate Exam |
| Exam Number: | Databricks-Certified-Data-Engineer-Associate |
| Exam Duration: | 90 minutes |
| Available Languages: | Portuguese (Brazil), Korean, Japanese, English |
| Passing Score: | Not publicly disclosed, approximately 70% |
| Certificate Validity Period: | 2 years |
| Real Exam Qty: | 45 |
| Exam Format: | Proctored, Multiple choice |
| Exam Price: | 200 USD |
| Related Certifications: | Databricks Certified Data Engineer Professional Databricks Certified Data Analyst Associate |
| Recommended Training: | Databricks Academy - Data Engineer Associate Learning Path Databricks Documentation |
| Exam Registration: | Official Registration |
| Sample Questions: | Databricks Databricks-Certified-Data-Engineer-Associate Sample Questions |
| Exam Way: | Online proctored or in-person at authorized test centers |
| Pre Condition: | No mandatory prerequisites; 6+ months hands-on experience with Databricks and data engineering tasks recommended |
| Official Syllabus URL: | https://www.databricks.com/learn/certification/data-engineer-associate |
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The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) Certification Exam is a comprehensive examination that tests the skills of professionals who work with data on the Databricks platform. Databricks Certified Data Engineer Associate Exam certification is designed for individuals who are responsible for designing, building, and maintaining data pipelines, as well as data analysts, data architects, and data engineers. The Databricks Certified Data Engineer Associate certification is recognized globally and validates the skills and knowledge of individuals in the field of data engineering.
NEW QUESTION # 182
A data engineer has a Job with multiple tasks that runs nightly. Each of the tasks runs slowly because the clusters take a long time to start.
Which of the following actions can the data engineer perform to improve the start up time for the clusters used for the Job?
Answer: E
Explanation:
Explanation
Cluster pools are a way to pre-provision clusters that are ready to use. This can reduce the start up time for clusters, as they do not have to be created from scratch. All-purpose clusters are not pre-provisioned, so they will take longer to start up. Jobs clusters are a type of cluster pool, but they are not the best option for this use case. Jobs clusters are designed for long-running jobs, and they can be more expensive than other types of cluster pools. Single-node clusters are the smallest type of cluster, and they will start up the fastest. However, they may not be powerful enough to run the Job's tasks. Autoscaling clusters can scale up or down based on demand. This can help to improve the start up time for clusters, as they will only be created when they are needed. However, autoscaling clusters can also be more expensive than other types of cluster pool
https://docs.databricks.com/en/clusters/pool-best-practices.html
NEW QUESTION # 183
A data engineer has left the organization. The data team needs to transfer ownership of the data engineer's Delta tables to a new data engineer. The new data engineer is the lead engineer on the data team.
Assuming the original data engineer no longer has access, which of the following individuals must be the one to transfer ownership of the Delta tables in Data Explorer?
Answer: D
Explanation:
The workspace administrator is the only individual who can transfer ownership of the Delta tables in Data Explorer, assuming the original data engineer no longer has access. The workspace administrator has the highest level of permissions in the workspace and can manage all resources, users, and groups. The other options are either not possible or not sufficient to perform the ownership transfer. The Databricks account representative is not involved in the workspace management. The transfer is possible and not dependent on the original data engineer. The new lead data engineer may not have the necessary permissions to access or modify the Delta tables, unless granted by the workspace administrator or the original data engineer before leaving. References: Workspace access control, Manage Unity Catalog object ownership.
NEW QUESTION # 184
A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table.
The cade block used by the data engineer is below:
If the data engineer only wants the query to execute a micro-batch to process data every 5 seconds, which of the following lines of code should the data engineer use to fill in the blank?
Answer: D
Explanation:
The processingTime option specifies a time-based trigger interval for fixed interval micro-batches. This means that the query will execute a micro-batch to process data every 5 seconds, regardless of how much data is available. This option is suitable for near-real time processing workloads that require low latency and consistent processing frequency. The other options are either invalid syntax (A, C), default behavior (B), or experimental feature (E). Reference: Databricks Documentation - Configure Structured Streaming trigger intervals, Databricks Documentation - Trigger.
NEW QUESTION # 185
A Delta Live Table pipeline includes two datasets defined using STREAMING LIVE TABLE. Three datasets are defined against Delta Lake table sources using LIVE TABLE.
The table is configured to run in Production mode using the Continuous Pipeline Mode.
Assuming previously unprocessed data exists and all definitions are valid, what is the expected outcome after clicking Start to update the pipeline?
Answer: C
Explanation:
1: In Production mode, the pipeline runs continuously and updates the output tables whenever new data is available in the input sources. The compute resources are allocated on demand and released when the pipeline is stopped. This mode is suitable for production workloads that require high availability and reliability. Reference: Configure pipeline settings for Delta Live Tables, Tutorial: Run your first Delta Live Tables pipeline, Building Reliable Data Pipelines Using DataBricks' Delta Live Tables
NEW QUESTION # 186
Which of the following Structured Streaming queries is performing a hop from a Silver table to a Gold table?
Answer: E
Explanation:
The best practice is to use "Complete" as output mode instead of "append" when working with aggregated tables. Since gold layer is work final aggregated tables, the only option with output mode as complete is option E.
NEW QUESTION # 187
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